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Williams J, Ahlqvist H, Cunningham A, Kirby A, Katz I, Fleming J, Conway J, Cunningham S, Ozel A, Wolfram U. Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks. PLoS One 2024; 19:e0297437. [PMID: 38277381 PMCID: PMC10817191 DOI: 10.1371/journal.pone.0297437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 01/04/2024] [Indexed: 01/28/2024] Open
Abstract
For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for patient-specific deposition modelling. To that end, an image processing approach is proposed that could produce 3D patient respiratory geometries from 2D chest X-rays and 3D CT images. We evaluated the airway and lung morphology produced by our image processing framework, and assessed deposition compared to in vivo data. The 2D-to-3D image processing reproduces airway diameter to 9% median error compared to ground truth segmentations, but is sensitive to outliers of up to 33% due to lung outline noise. Predicted regional deposition gave 5% median error compared to in vivo measurements. The proposed framework is capable of providing patient-specific deposition measurements for varying treatments, to determine which treatment would best satisfy the needs imposed by each patient (such as disease and lung/airway morphology). Integration of patient-specific modelling into clinical practice as an additional decision-making tool could optimise treatment plans and lower the burden of respiratory diseases.
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Affiliation(s)
- Josh Williams
- School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, United Kingdom
- Hartree Centre, STFC Daresbury Laboratory, Daresbury, United Kingdom
| | - Haavard Ahlqvist
- School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, United Kingdom
| | - Alexander Cunningham
- School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, United Kingdom
| | - Andrew Kirby
- Royal Hospital for Children and Young People, NHS Lothian, Edinburgh, United Kingdom
| | | | - John Fleming
- National Institute of Health Research Biomedical Research Centre in Respiratory Disease, Southampton, United Kingdom
- Department of Medical Physics and Bioengineering, University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Joy Conway
- National Institute of Health Research Biomedical Research Centre in Respiratory Disease, Southampton, United Kingdom
- Respiratory Sciences, Centre for Health and Life Sciences, Brunel University, London, United Kingdom
| | - Steve Cunningham
- Centre for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom
| | - Ali Ozel
- School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, United Kingdom
| | - Uwe Wolfram
- School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, United Kingdom
- Institute for Material Science and Engineering, TU Clausthal, Clausthal-Zellerfeld, Germany
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Evaluation of Impulse Oscillometry in Respiratory Airway Casts with Varying Obstruction Phenotypes, Locations, and Complexities. JOURNAL OF RESPIRATION 2022. [DOI: 10.3390/jor2010004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
The use of impulse oscillometry (IOS) for lung function testing does not need patient cooperation and has gained increasing popularity among both young and senior populations, as well as in patients with breathing difficulties. However, studies of the IOS sensitivity to regional lung obstructions are limited and have shown mixed results. The objective of this study was to evaluate the performance of an IOS system in 3D-printed lung models with structural abnormalities at different locations and with different severities. Lung trees of two complexity levels were tested, with one extending to the sixth generation (G6) and the other to G12. The IOS responses to varying glottal apertures, carina ridge tumors, and segmental bronchial constrictions were quantified in the G6 lung geometry. Both the G6 and G12 lung casts were prepared using high-resolution 3D printers. Overall, IOS detected the progressive airway obstructions considered in this study. The resonant frequency dropped with increasing obstructions for all three disease phenotypes in the G6 lung models. R20Hz increased with the increase in airway obstructions. Specifically, R20Hz in the airway model with varying glottal apertures agreed reasonably well with complementary measurements using TSI VelociCalc. In contrast to the high-resistance (R) sensitivity to the frequency in G6 lung models, R was nearly independent of frequency in G12 lung models. IOS R20Hz demonstrated adequate sensitivity to the structural remodeling in the central airways. However, the changes of R5Hz and X5Hz vs. airway obstructions were inconclusive in this study, possibly due to the rigid lung casts and the difference of a container–syringe system from human lungs.
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Grassi L, Väänänen SP, Isaksson H. Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care. Curr Osteoporos Rep 2021; 19:676-687. [PMID: 34773211 PMCID: PMC8716351 DOI: 10.1007/s11914-021-00711-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/27/2021] [Indexed: 11/27/2022]
Abstract
PURPOSE OF REVIEW Statistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation. RECENT FINDINGS Recent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. All the reviewed application areas made considerable steps forward in the past 5-6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.
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Affiliation(s)
- Lorenzo Grassi
- Department of Biomedical Engineering, Lund University, Box 118, 221 00, Lund, Sweden.
| | - Sami P Väänänen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
- Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Hanna Isaksson
- Department of Biomedical Engineering, Lund University, Box 118, 221 00, Lund, Sweden
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Talaat M, Si XA, Dong H, Xi J. Leveraging statistical shape modeling in computational respiratory dynamics: Nanomedicine delivery in remodeled airways. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 204:106079. [PMID: 33831725 DOI: 10.1016/j.cmpb.2021.106079] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 03/29/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND AND OBJECTIVE Accurate knowledge of the delivered doses to the diseased site in the respiratory tract is crucial to elicit desired therapeutic outcomes. However, such information is still difficult to obtain due to inaccessibility for measurement or visualization, complex network structure, and challenges in reconstructing lung geometries with disease-invoked airway remodeling. This study presents a novel method to simulate the airway remodeling in a mouth-lung geometry extending to G9. METHODS Statistical shape modeling was used to extract morphological features from a lung geometry database and four new models (i.e., M1-M4) were generated with parameter-controlled dilated/constricted bronchioles in the left-lower (LL) lung. The variations in airflow and particle deposition due to the airway remodeling were simulated using a well-tested k-ω turbulence model and a Lagrangian tracking approach. RESULTS Significant variations in flow partitions between the lower and upper lobes of the left lung, as well as between the left and right lungs. The flow partition into the LL lobe varied by 10-fold between the most dilated and constricted models in this study. Significantly lower doses were also predicted on the surface of the constricted LL bronchioles G4-G9, as well as into the peripheral airways beyond G9. However, the total dosimetry in the mouth-lung geometry (up to G9) exhibited low sensitivity to the LL lobar remodeling. Results in this study suggest that the optimal nanomedicine should be 2-10 nm in diameter if targeted at the constricted bronchioles G4-G9 as in topical inhalation therapy but should be larger than 20 nm if targeted at the alveolar region as in systemic therapy. CONCLUSIONS This study highlights the large dose variability from local airway remodeling and the need to consider these variations in the treatment planning for pneumonia and other obstructive respiratory diseases.
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Affiliation(s)
- Mohamed Talaat
- Department of Biomedical Engineering, University of Massachusetts, Lowell, MA, U.S.A.
| | - Xiuhua April Si
- Department of Aerospace, Industrial, and Mechanical Engineering, California Baptist University, Riverside, CA, U.S.A.
| | - Haibo Dong
- Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, U.S.A.
| | - Jinxiang Xi
- Department of Biomedical Engineering, University of Massachusetts, Lowell, MA, U.S.A.
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Si XA, Talaat M, Su WC, Xi J. Inhalation dosimetry of nasally inhaled respiratory aerosols in the human respiratory tract with locally remodeled conducting lungs. Inhal Toxicol 2021; 33:143-159. [PMID: 33870835 DOI: 10.1080/08958378.2021.1912860] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Objective: Respiratory diseases are often accompanied by alterations to airway morphology. However, inhalation dosimetry data in remodeled airways are scarce due to the challenges in reconstructing diseased respiratory morphologies. This study aims to study the airway remodeling effects on the inhalation dosimetry of nasally inhaled nanoparticles in a nose-lung geometry that extends to G9 (ninth generation).Materials and methods: Statistical shape modeling was used to develop four diseased lung models with varying levels of bronchiolar dilation/constriction in the left-lower (LL) lobe (i.e. M1-M4). Respiratory airflow and particle deposition were simulated using a low Reynolds number k-ω turbulence model and a Lagrangian tracking approach.Results: Significant discrepancies were observed in the flow partitions between the left and right lungs, as well as between the lower and upper lobes of the left lung, which changed by 10-fold between the most dilated and constricted models.Much lower doses were predicted on the surface of the constricted LL bronchioles G4-G9, as well as into the peripheral airways beyond G9 of the LL lung. However, the LL lobar remodeling had little effect on the dosimetry in the nasopharynx, as well as on the total dosimetry in the nose-lung geometry (up to G9).Conclusion: It is suggested that airway remodeling may pose a higher viral infection risk to the host by redistributing the inhaled viruses to healthy lung lobes. Airway remodeling effects should also be considered in the treatment planning of inhalation therapies, not only because of the dosimetry variation from altered lung morphology but also its evolution as the disease progresses.
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Affiliation(s)
- Xiuhua April Si
- Department of Mechanical Engineering, California Baptist University, Riverside, CA, USA
| | - Mohamed Talaat
- Department of Biomedical Engineering, University of Massachusetts, Lowell, MA, USA
| | - Wei-Chung Su
- Department of Epidemiology, Human Genetics, and Environmental Science, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jinxiang Xi
- Department of Biomedical Engineering, University of Massachusetts, Lowell, MA, USA
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Aldieri A, Terzini M, Audenino AL, Bignardi C, Morbiducci U. Combining shape and intensity dxa-based statistical approaches for osteoporotic HIP fracture risk assessment. Comput Biol Med 2020; 127:104093. [PMID: 33130436 DOI: 10.1016/j.compbiomed.2020.104093] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 10/23/2020] [Accepted: 10/23/2020] [Indexed: 10/23/2022]
Abstract
Aiming to improve osteoporotic hip fracture risk detection, factors other than the largely adopted Bone Mineral Density (BMD) have been investigated as potential risk predictors. In particular Hip Structural Analysis (HSA)-derived parameters accounting for femur geometry, extracted from Dual-energy X-ray Absorptiometry (DXA) images, have been largely considered as geometric risk factors. However, HSA-derived parameters represent discrete and cross-correlated quantities, unable to describe proximal femur geometry as a whole and tightly related to BMD. Focusing on a post-menopausal cohort (N = 28), in this study statistical models of bone shape and BMD distribution have been developed to investigate their possible role in fracture risk. Due to unavailable retrospective patient-specific fracture risk information, here a surrogate fracture risk based on 3D computer simulations has been employed for the statistical framework construction. When considered separately, BMD distribution performed better than shape in explaining the surrogate fracture risk variability for the analysed cohort. However, the combination of BMD and femur shape quantities in a unique statistical model yielded better results. In detail, the first shape-intensity combined mode identified using a Partial Least Square (PLS) algorithm was able to explain 70% of the surrogate fracture risk variability, thus suggesting that a more effective patients stratification can be obtained applying a shape-intensity combination approach, compared to T-score. The findings of this study strongly advocate future research on the role of a combined shape-BMD statistical framework in fracture risk determination.
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Affiliation(s)
- Alessandra Aldieri
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PolitoBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Mara Terzini
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PolitoBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Alberto L Audenino
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PolitoBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Cristina Bignardi
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PolitoBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Umberto Morbiducci
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PolitoBIOMed Lab, Politecnico di Torino, Turin, Italy.
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Deane JA, Pavlova AV, Lim AKP, Gregory JS, Aspden RM, McGregor AH. Is intrinsic lumbar spine shape associated with lumbar disc degeneration? An exploratory study. BMC Musculoskelet Disord 2020; 21:433. [PMID: 32620099 PMCID: PMC7334848 DOI: 10.1186/s12891-020-03346-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 05/13/2020] [Indexed: 11/15/2022] Open
Abstract
Background Lumbar disc degeneration (LDD) is a condition associated with recurrent low back pain (LBP). Knowledge regarding effective management is limited. As a step towards the identification of risk, prognostic or potentially modifiable factors in LDD patients, the aim of this study was to explore the hypothesis that intrinsic lumbar spine shape is associated with LDD and clinical outcomes in symptomatic adults. Methods 3 T MRI was used to acquire T2-weighted sagittal images (L1-S1) from 70 healthy controls and LDD patients (mean age 49 years, SD 11, range 31–71 years). Statistical Shape Modelling (SSM) was used to describe lumbar spine shape. SSM identified variations in lumbar shape as ‘modes’ of variation and quantified deviation from the mean. Intrinsic shape differences were determined between LDD groups using analysis of variance with post-hoc comparisons. The relationship between intrinsic shape and self-reported function, mental health and quality of life were also examined. Results The first 7 modes of variation explained 91% of variance in lumbar shape. Higher LDD sum scores correlated with a larger lumbar lordosis (Mode 1 (55% variance), P = 0.02), even lumbar curve distribution (Mode 2 (12% variance), P = 0.05), larger anterior-posterior (A-P) vertebral diameter (Mode 3 (10% variance), P = 0.007) and smaller L4-S1 disc spaces (Mode 7 (2% variance), P ≤ 0.001). In the presence of recurrent LBP, LDD was associated with a larger A-P vertebral diameter (Mode 3) and a more even lumbar curvature with smaller L5/S1 disc spaces (Mode 4), which was significantly associated with patient quality of life (P = 0.002–0.04, rp = 0.43–0.61)). Conclusions This exploratory study provides new evidence that intrinsic shape phenotypes are associated with LDD and quality of life in patients. Longitudinal studies are required to establish the potential role of these risk or prognostic shape phenotypes.
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Affiliation(s)
- Janet A Deane
- Sackler MSK LAB, Sir Michael Uren Hub, Imperial College London, White City Campus, 86 Wood Lane, London, W12 0BZ, UK. .,Imaging Department, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
| | - Anastasia V Pavlova
- Aberdeen Centre for Arthritis and Musculoskeletal Health, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Adrian K P Lim
- Imaging Department, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK
| | - Jennifer S Gregory
- Aberdeen Centre for Arthritis and Musculoskeletal Health, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Richard M Aspden
- Aberdeen Centre for Arthritis and Musculoskeletal Health, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Alison H McGregor
- Sackler MSK LAB, Sir Michael Uren Hub, Imperial College London, White City Campus, 86 Wood Lane, London, W12 0BZ, UK
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Wani IM, Arora S. Computer-aided diagnosis systems for osteoporosis detection: a comprehensive survey. Med Biol Eng Comput 2020; 58:1873-1917. [PMID: 32583141 DOI: 10.1007/s11517-020-02171-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 03/26/2020] [Indexed: 12/18/2022]
Abstract
Computer-aided diagnosis (CAD) has revolutionized the field of medical diagnosis. They assist in improving the treatment potentials and intensify the survival frequency by early diagnosing the diseases in an efficient, timely, and cost-effective way. The automatic segmentation has led the radiologist to successfully segment the region of interest to improve the diagnosis of diseases from medical images which is not so efficiently possible by manual segmentation. The aim of this paper is to survey the vision-based CAD systems especially focusing on the segmentation techniques for the pathological bone disease known as osteoporosis. Osteoporosis is the state of the bones where the mineral density of bones decreases and they become porous, making the bones easily susceptible to fractures by small injury or a fall. The article covers the image acquisition techniques for acquiring the medical images for osteoporosis diagnosis. The article also discusses the advanced machine learning paradigms employed in segmentation for osteoporosis disease. Other image processing steps in osteoporosis like feature extraction and classification are also briefly described. Finally, the paper gives the future directions to improve the osteoporosis diagnosis and presents the proposed architecture. Graphical abstract.
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Affiliation(s)
- Insha Majeed Wani
- School of Computer Science and Engineering, SMVDU, Katra, J&K, India
| | - Sakshi Arora
- School of Computer Science and Engineering, SMVDU, Katra, J&K, India.
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Dicuonzo F, Purciariello S, Andresciani S, De Marco A, Colamaria A, Calace A. "Less is better"-always true? Neurol Sci 2019; 41:41-47. [PMID: 31399879 DOI: 10.1007/s10072-019-04016-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 07/17/2019] [Indexed: 10/26/2022]
Abstract
OBJECTIVE The aim of the study is to try to explain what an overtreatment is and which ones are the possible risks related to an excess of simplification in the medical practice, through the description of an emblematic clinical case. METHODS In the present article, we report the case of a female patient aged 57 who complained about lower back pain and crural neuralgia and had a lumbar and sacral magnetic resonance imaging performed in the Department of Neuroradiology in Bari showing suspicious repetitive bone lesions; therefore, the patient underwent several medical procedures and laboratory exams which ended with a surgical removal of a left L3-L4 foraminal disc herniation and a bone biopsy. RESULTS When it was finally possible to exclude any other diseases including thyroid neoplasms, a "reassuring" osteoporosis diagnosis has been made since the lesions were likely to be degenerative and the patient underwent menopause 7 years ago. However, the multiplicity of the lesions of the vertebrae and of the pelvic bones as well as their signal could not be ignored, so that a close magnetic resonance imaging follow-up has been recommended. CONCLUSIONS The present case is therefore a good example of overtreatment which may lead to delicate questions, investigating any possible mistakes in the diagnosis procedure as well as the role that defensive medicine is playing nowadays on medical procedures and the economic impact that all this can have on our healthcare system. In the end, we may ask ourselves: is "less" better or is "more" always "more?"
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Affiliation(s)
- Franca Dicuonzo
- Department of Neuroradiology, School of Medicine, Department of Basic Med Sci Neurosci & Sense Organs, School of Medicine, University of Bari "Aldo Moro", Bari, Italy. .,Department of Neuroradiology, School of Medicine, Department of Basic Med Sci Neurosci & Sense Organs, School of Medicine, University of Bari "Aldo Moro", School of Medicine, Piazza Giulio Cesare, 11, 70124, Bari, BA, Italy.
| | - Stefano Purciariello
- Department of Neuroradiology, School of Medicine, Department of Basic Med Sci Neurosci & Sense Organs, School of Medicine, University of Bari "Aldo Moro", Bari, Italy
| | - Stefano Andresciani
- Department of Neuroradiology, School of Medicine, Department of Basic Med Sci Neurosci & Sense Organs, School of Medicine, University of Bari "Aldo Moro", Bari, Italy
| | - Aurora De Marco
- Department of Neuroradiology, School of Medicine, Department of Basic Med Sci Neurosci & Sense Organs, School of Medicine, University of Bari "Aldo Moro", Bari, Italy
| | - Antonio Colamaria
- Department of Neurosurgery, School of Medicine, Department of Basic Med Sci Neurosci & Sense Organs, School of Medicine, University of Bari "Aldo Moro", Bari, Italy
| | - Antonio Calace
- Department of Neurosurgery, School of Medicine, Department of Basic Med Sci Neurosci & Sense Organs, School of Medicine, University of Bari "Aldo Moro", Bari, Italy
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Duque-Domingo J, Herrera PJ, Valero E, Cerrada C. Deciphering Egyptian Hieroglyphs: Towards a New Strategy for Navigation in Museums. SENSORS 2017; 17:s17030589. [PMID: 28335445 PMCID: PMC5375875 DOI: 10.3390/s17030589] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 03/10/2017] [Accepted: 03/10/2017] [Indexed: 11/26/2022]
Abstract
This work presents a novel strategy to decipher fragments of Egyptian cartouches identifying the hieroglyphs of which they are composed. A cartouche is a drawing, usually inside an oval, that encloses a group of hieroglyphs representing the name of a monarch. Aiming to identify these drawings, the proposed method is based on several techniques frequently used in computer vision and consists of three main stages: first, a picture of the cartouche is taken as input and its contour is localized. In the second stage, each hieroglyph is individually extracted and identified. Finally, the cartouche is interpreted: the sequence of the hieroglyphs is established according to a previously generated benchmark. This sequence corresponds to the name of the king. Although this method was initially conceived to deal with both high and low relief writing in stone, it can be also applied to painted hieroglyphs. This approach is not affected by variable lighting conditions, or the intensity and the completeness of the objects. This proposal has been tested on images obtained from the Abydos King List and other Egyptian monuments and archaeological excavations. The promising results give new possibilities to recognize hieroglyphs, opening a new way to decipher longer texts and inscriptions, being particularly useful in museums and Egyptian environments. Additionally, devices used for acquiring visual information from cartouches (i.e., smartphones), can be part of a navigation system for museums where users are located in indoor environments by means of the combination of WiFi Positioning Systems (WPS) and depth cameras, as unveiled at the end of the document.
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Affiliation(s)
- Jaime Duque-Domingo
- Depto.de Ingeniería de Software y Sistemas Informáticos, ETSI Informática, UNED. C/Juan del Rosal, 16, 28040 Madrid, Spain.
| | - Pedro Javier Herrera
- Depto.de Ingeniería de Software y Sistemas Informáticos, ETSI Informática, UNED. C/Juan del Rosal, 16, 28040 Madrid, Spain.
| | - Enrique Valero
- School of Energy, Geoscience, Infrastructure and Society, Heriott-Watt University, Edinburgh EH14 4AS, UK.
| | - Carlos Cerrada
- Depto.de Ingeniería de Software y Sistemas Informáticos, ETSI Informática, UNED. C/Juan del Rosal, 16, 28040 Madrid, Spain.
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Abstract
PURPOSE OF REVIEW This paper seeks to evaluate and compare recent advances in the clinical assessment of the changes in bone mechanical properties that take place as a result of osteoporosis and other metabolic bone diseases and their treatments. RECENT FINDINGS In addition to the standard of DXA-based areal bone mineral density (aBMD), a variety of methods, including imaging-based structural measurements, finite element analysis (FEA)-based techniques, and alternate methods including ultrasound, bone biopsy, reference point indentation, and statistical shape and density modeling, have been developed which allow for reliable prediction of bone strength and fracture risk. These methods have also shown promise in the evaluation of treatment-induced changes in bone mechanical properties. Continued technological advances allowing for increasingly high-resolution imaging with low radiation dose, together with the expanding adoption of DXA-based predictions of bone structure and mechanics, as well as the increasing awareness of the importance of bone material properties in determining whole-bone mechanics, lead us to anticipate substantial future advances in this field.
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Affiliation(s)
- Chantal M J de Bakker
- McKay Orthopaedic Research Laboratory, Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, 426C Stemmler Hall, 36th Street and Hamilton Walk, Philadelphia, PA, 19104, USA
| | - Wei-Ju Tseng
- McKay Orthopaedic Research Laboratory, Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, 426C Stemmler Hall, 36th Street and Hamilton Walk, Philadelphia, PA, 19104, USA
| | - Yihan Li
- McKay Orthopaedic Research Laboratory, Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, 426C Stemmler Hall, 36th Street and Hamilton Walk, Philadelphia, PA, 19104, USA
| | - Hongbo Zhao
- McKay Orthopaedic Research Laboratory, Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, 426C Stemmler Hall, 36th Street and Hamilton Walk, Philadelphia, PA, 19104, USA
| | - X Sherry Liu
- McKay Orthopaedic Research Laboratory, Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, 426C Stemmler Hall, 36th Street and Hamilton Walk, Philadelphia, PA, 19104, USA.
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Grassi L, Väänänen SP, Ristinmaa M, Jurvelin JS, Isaksson H. Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments. Biomech Model Mechanobiol 2016; 16:989-1000. [PMID: 28004226 PMCID: PMC5422489 DOI: 10.1007/s10237-016-0866-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 12/10/2016] [Indexed: 12/01/2022]
Abstract
Computed tomography (CT)-based finite element (FE) models may improve the current osteoporosis diagnostics and prediction of fracture risk by providing an estimate for femoral strength. However, the need for a CT scan, as opposed to the conventional use of dual-energy X-ray absorptiometry (DXA) for osteoporosis diagnostics, is considered a major obstacle. The 3D shape and bone mineral density (BMD) distribution of a femur can be reconstructed using a statistical shape and appearance model (SSAM) and the DXA image of the femur. Then, the reconstructed shape and BMD could be used to build FE models to predict bone strength. Since high accuracy is needed in all steps of the analysis, this study aimed at evaluating the ability of a 3D FE model built from one 2D DXA image to predict the strains and fracture load of human femora. Three cadaver femora were retrieved, for which experimental measurements from ex vivo mechanical tests were available. FE models were built using the SSAM-based reconstructions: using only the SSAM-reconstructed shape, only the SSAM-reconstructed BMD distribution, and the full SSAM-based reconstruction (including both shape and BMD distribution). When compared with experimental data, the SSAM-based models predicted accurately principal strains (coefficient of determination >0.83, normalized root-mean-square error <16%) and femoral strength (standard error of the estimate 1215 N). These results were only slightly inferior to those obtained with CT-based FE models, but with the considerable advantage of the models being built from DXA images. In summary, the results support the feasibility of SSAM-based models as a practical tool to introduce FE-based bone strength estimation in the current fracture risk diagnostics.
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Affiliation(s)
- Lorenzo Grassi
- Department of Biomedical Engineering, Lund University, BMC D13, 221 84, Lund, Sweden.
| | - Sami P Väänänen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
- Department of Orthopaedics, Traumatology and Hand Surgery, Kuopio University Hospital, Kuopio, Finland
| | | | - Jukka S Jurvelin
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
- Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Hanna Isaksson
- Department of Biomedical Engineering, Lund University, BMC D13, 221 84, Lund, Sweden
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Frangi AF, Taylor ZA, Gooya A. Precision Imaging: more descriptive, predictive and integrative imaging. Med Image Anal 2016; 33:27-32. [PMID: 27373145 DOI: 10.1016/j.media.2016.06.024] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Revised: 06/15/2016] [Accepted: 06/15/2016] [Indexed: 12/22/2022]
Abstract
Medical image analysis has grown into a matured field challenged by progress made across all medical imaging technologies and more recent breakthroughs in biological imaging. The cross-fertilisation between medical image analysis, biomedical imaging physics and technology, and domain knowledge from medicine and biology has spurred a truly interdisciplinary effort that stretched outside the original boundaries of the disciplines that gave birth to this field and created stimulating and enriching synergies. Consideration on how the field has evolved and the experience of the work carried out over the last 15 years in our centre, has led us to envision a future emphasis of medical imaging in Precision Imaging. Precision Imaging is not a new discipline but rather a distinct emphasis in medical imaging borne at the cross-roads between, and unifying the efforts behind mechanistic and phenomenological model-based imaging. It captures three main directions in the effort to deal with the information deluge in imaging sciences, and thus achieve wisdom from data, information, and knowledge. Precision Imaging is finally characterised by being descriptive, predictive and integrative about the imaged object. This paper provides a brief and personal perspective on how the field has evolved, summarises and formalises our vision of Precision Imaging for Precision Medicine, and highlights some connections with past research and current trends in the field.
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Affiliation(s)
- Alejandro F Frangi
- CISTIB Centre for Computational Imaging & Simulation Technologies in Biomedicine, Electronic and Electrical Engineering Department, University of Sheffield, Sheffield, UK.
| | - Zeike A Taylor
- CISTIB Centre for Computational Imaging & Simulation Technologies in Biomedicine, Mechanical Engineering Department, University of Sheffield, Sheffield, UK.
| | - Ali Gooya
- CISTIB Centre for Computational Imaging & Simulation Technologies in Biomedicine, Electronic and Electrical Engineering Department, University of Sheffield, Sheffield, UK.
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